Automatic Image Based Object Damage Assessment

Abstract

The present invention provides a computer-based method for automatically evaluating validity and extent of at least one damaged object from image data, comprising the steps of: (a) receive image data comprising one or more images of at least one damaged object; (b) inspect any one of said one or more images for existing image alteration utilising an image alteration detection algorithm, and remove any image comprising image alterations from said one or more images; (c) identify and classify said at least one damaged object in any one of said one or more images, utilising at least one first machine learning algorithm; (d) detect at least one damaged area of said classified damaged object, utilising at least one second machine learning algorithm; (e) classify, quantitatively and / or qualitatively, an extent of damage of said at least one damaged area, utilising at least one third machine learning algorithm, and characteristic information of said damaged object and / or an undamaged object that is at least equivalent to said at least one damaged object; (f) provide a visual marker to said detected at least one damaged area in any one of said at least one or more images; (g) generate a predictive analysis to repair and / or replace said at least one damaged object, utilising a fourth machine learning algorithm and said classified extent of damage of the detected said at least one damaged area.

Description

[0001]The present invention relates to systems and methods for detecting / analysing / assessing damage to an object such as, for example, a vehicle and providing estimates on repair / replacement costs, as well as, an evaluation on potential image manipulation and fraud. In particular, the present invention relates to a fully automated method for detecting / analysing / assessing damage to an object from image data provided by a user.INTRODUCTION[0002]When insured property is damaged, the owner may file a claim with the insurance company. However, conventional processing of the insurance claim is a complex process including, inter alia, the involvement of experts such as accident assessors in order to inspect, analyse and assess any damage to the insured object and provide the amount of damage, as well as, costs required to repair or replace the damaged object. Thus, there is a heavy reliance on manual inspections by an expert to provide a repair cost estimate, which may come with significan...

AI Technical Summary

Benefits of technology

The present invention provides a computer-based method for automatically evaluating damage to objects using image data. The method uses machine learning algorithms to detect and classify damage in images of damaged objects, and to quantitatively and qualitatively evaluate the extent of damage. The method can also use non-technical images and predict the implications of the damage, such as the cost of repair or the likelihood of fraud. The system can also be easily re-trained for different industries and can detect fraudulent activities. The method and system provide an efficient and accurate way to assess damage and make informed decisions in the insurance claim lifecycle.

Problems solved by technology

When insured property is damaged, the owner may file a claim with the insurance company.

However, conventional processing of the insurance claim is a complex process including, inter alia, the involvement of experts such as accident assessors in order to inspect, analyse and assess any damage to the insured object and provide the amount of damage, as well as, costs required to repair or replace the damaged object.

Thus, there is a heavy reliance on manual inspections by an expert to provide a repair cost estimate, which may come with significant cost and delay in processing time, as a person (assessor) must view the asset in order to assess the damage and decide upon an outcome, e.g. view a vehicle and decide if the vehicle is repairable or not.

This is a costly, time consuming process particularly when there are finite technical resources.

Other available systems may allow a consumer to capture the images in accordance with strict instructions and process the initial claim by providing detailed information of the damage (e.g. following a protocol of questions to determine the location, type and description of the damage), making the process very time consuming and very subjective to the consumer's incentive.

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